Description

Book Synopsis
Available for the first time in McGraw-Hill''s Connect! Principles of Statistics for Engineers and Scientists emphasizes statistical methods and how they can be applied to problems in science and engineering. The book contains many examples that feature real, contemporary data sets, both to motivate students and to show connections to industry and scientific research. Because statistical analyses are done on computers, the book contains exercises and examples that involve interpreting, as well as generating, computer output. This book may be used effectively with any software package.

Table of Contents
1 Summarizing Univariate Data2 Summarizing Bivariate Data3 Probability4 Commonly Used Distributions5 Point and Interval Estimation for a Single Sample6 Hypothesis Tests for a Single Sample7 Inferences for Two Samples8 Inference in Linear Models9 Factorial Experiments10 Statistical Quality Control

ISE Principles of Statistics for Engineers and

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    A Paperback / softback by William Navidi

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      Publisher: McGraw-Hill Education
      Publication Date: 23/03/2020
      ISBN13: 9781260570731, 978-1260570731
      ISBN10: 1260570738

      Description

      Book Synopsis
      Available for the first time in McGraw-Hill''s Connect! Principles of Statistics for Engineers and Scientists emphasizes statistical methods and how they can be applied to problems in science and engineering. The book contains many examples that feature real, contemporary data sets, both to motivate students and to show connections to industry and scientific research. Because statistical analyses are done on computers, the book contains exercises and examples that involve interpreting, as well as generating, computer output. This book may be used effectively with any software package.

      Table of Contents
      1 Summarizing Univariate Data2 Summarizing Bivariate Data3 Probability4 Commonly Used Distributions5 Point and Interval Estimation for a Single Sample6 Hypothesis Tests for a Single Sample7 Inferences for Two Samples8 Inference in Linear Models9 Factorial Experiments10 Statistical Quality Control

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